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Record W4296328016 · doi:10.1213/ane.0000000000006192

Pulmonary Vasodilator Response of Combined Inhaled Epoprostenol and Inhaled Milrinone in Cardiac Surgical Patients

2022· article· en· W4296328016 on OpenAlexaffabout
Mahsa Elmi-Sarabi, Stéphanie Jarry, Étienne J. Couture, François Haddad, Jennifer Cogan, Andrew J. Sweatt, Nicolas Rousseau‐Saine, William Beaubien‐Souligny, Annik Fortier, André Denault

Bibliographic record

VenueAnesthesia & Analgesia · 2022
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité de MontréalUniversité LavalMontreal Heart Institute
Fundersnot available
KeywordsMedicinePulmonary arteryMilrinoneAnesthesiaPerioperativeCardiologyCardiopulmonary bypassAfterloadInternal medicinePulmonary hypertensionCardiac surgeryVascular resistanceHemodynamics

Abstract

fetched live from OpenAlex

BACKGROUND: Pulmonary hypertension (PH) and right ventricular (RV) dysfunction are major complications in cardiac surgery. Intraoperative management of patients at high risk of RV failure should aim to reduce RV afterload and optimize RV filling pressures, while avoiding systemic hypotension, to facilitate weaning from cardiopulmonary bypass (CPB). Inhaled epoprostenol and inhaled milrinone (iE&iM) administered in combination before CPB may represent an effective strategy to facilitate separation from CPB and reduce requirements for intravenous inotropes during cardiac surgery. Our primary objective was to report the rate of positive pulmonary vasodilator response to iE&iM and, second, how it relates to perioperative outcomes in cardiac surgery. METHODS: This is a retrospective cohort study of consecutive patients with PH or RV dysfunction undergoing on-pump cardiac surgery at the Montreal Heart Institute from July 2013 to December 2018 (n = 128). iE&iM treatment was administered using an ultrasonic mesh nebulizer before the initiation of CPB. Demographic and baseline clinical data, as well as hemodynamic, intraoperative, and echocardiographic data, were collected using electronic records. An increase of 20% in the mean arterial pressure (MAP) to mean pulmonary artery pressure (MPAP) ratio was used to indicate a positive response to iE&iM. RESULTS: In this cohort, 77.3% of patients were responders to iE&iM treatment. Baseline systolic pulmonary artery pressure (SPAP) (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.24-2.16 per 5 mm Hg; P = .0006) was found to be a predictor of pulmonary vasodilator response, while a European System for Cardiac Operative Risk Evaluation (EuroSCORE II) score >6.5% was a predictor of nonresponse to treatment (≤6.5% vs >6.5% [reference]: OR, 5.19; 95% CI, 1.84-14.66; P = .002). Severity of PH was associated with a positive response to treatment, where a higher proportion of responders had MPAP values >30 mm Hg (42.4% responders vs 24.1% nonresponders; P = .0237) and SPAP values >55 mm Hg (17.2% vs 3.4%; P = .0037). Easier separation from CPB was also associated with response to iE&iM treatment (69.7% vs 58.6%; P = .0181). A higher proportion of nonresponders had a very difficult separation from CPB and required intravenous inotropic drug support compared to responders, for whom easy separation from CPB was more frequent. Use of intravenous inotropes after CPB was lower in responders to treatment (8.1% vs 27.6%; P = .0052). CONCLUSIONS: A positive pulmonary vasodilator response to treatment with a combination of iE&iM before initiation of CPB was observed in 77% of patients. Higher baseline SPAP was an independent predictor of pulmonary vasodilator response, while EuroSCORE II >6.5% was a predictor of nonresponse to treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.245
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations20
Published2022
Admission routes2
Has abstractyes

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